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dplyr modifying operations

Source: R/dtrackr.R
rename_with.trackr_df.Rd

See dplyr::mutate(), dplyr::add_count(), dplyr::add_tally(), dplyr::transmute(), dplyr::select(), dplyr::relocate(), dplyr::rename() dplyr::rename_with(), dplyr::arrange() for more details on underlying functions. dtrackr provides equivalent functions for mutating, selecting and renaming a data set which act in the same way as dplyr. mutate / select / rename generally don't add anything in terms of provenance of data so the default behaviour is to miss these out of the dtrackr history. This can be overridden with the .messages, or .headline values in which case they behave just like a comment().

Usage

# S3 method for class 'trackr_df'
rename_with(.data, ..., .messages = "", .headline = "", .tag = NULL)

Arguments

.data

A data frame, data frame extension (e.g. a tibble), or a lazy data frame (e.g. from dbplyr or dtplyr). See Methods, below, for more details.

...

<data-masking> Name-value pairs. The name gives the name of the column in the output.

The value can be:

  • A vector of length 1, which will be recycled to the correct length.

  • A vector the same length as the current group (or the whole data frame if ungrouped).

  • NULL, to remove the column.

  • A data frame or tibble, to create multiple columns in the output.

Named arguments passed on to dplyr::rename_with

.fn

A function used to transform the selected .cols. Should return a character vector the same length as the input.

.cols

<tidy-select> Columns to rename; defaults to all columns.

.messages

a set of glue specs. The glue code can use any global variable, grouping variable, {.new_cols} or {.dropped_cols} for changes to columns, {.cols} for the output column names, or {.strata}. Defaults to nothing.

.headline

a headline glue spec. The glue code can use any global variable, grouping variable, {.new_cols}, {.dropped_cols}, {.cols} or {.strata}. Defaults to nothing.

.tag

if you want the summary data from this step in the future then give it a name with .tag.

Value

the .data dataframe after being modified by the dplyr equivalent function, but with the history graph updated with a new stage if the .messages or .headline parameter is not empty.

See also

dplyr::rename_with()

Examples

library(dplyr)
library(dtrackr)

# mutate and other functions are unitary operations that generally change
# the structure but not size of a dataframe. In dtrackr these are by ignored
# by default but we can change that so that their behaviour is obvious.

# rename can show us which columns are new and which have been
# removed (with .dropped_cols)
iris %>%
  track() %>%
  group_by(Species) %>%
  rename(
    Stamen.Width = Sepal.Width,
    Stamen.Length = Sepal.Length,
    .messages=c("added {.new_cols}","dropped {.dropped_cols}"),
    .headline="Renamed columns:") %>%
  history()
#> dtrackr history:
#> number of flowchart steps: 3 (approx)
#> tags defined: <none>
#> items excluded so far: <not capturing exclusions>
#> last entry / entries:
#> ├ [Species:setosa]: "Renamed columns:", "added Stamen.Length, Stamen.Width", "dropped Sepal.Length, Sepal.Width"
#> ├ [Species:versicolor]: "Renamed columns:", "added Stamen.Length, Stamen.Width", "dropped Sepal.Length, Sepal.Width"
#> └ [Species:virginica]: "Renamed columns:", "added Stamen.Length, Stamen.Width", "dropped Sepal.Length, Sepal.Width"